Abstract

In the current scenario, the fast growth and demands for remote sensing databases combined with human limits to analyze and extract knowledge from huge datasets lead to a need to investigate tools, techniques, methodologies, and theories capable of assisting humans. Image mining arises as a solution to extract implicit knowledge intelligently in huge image databases. Due to the growth in the volume of spatial information which is produced many times a day, demands other means for knowledge extraction. Spatial databases are among the ones with the fastest growth for investigation. Multiagent systems are composed of multiple computing elements known as agents that interact to pursue their goals. Agents have been used to explore information in distributed, open, large, and heterogeneous platforms. To solve relevant issues more precisely, accurately, and fastly, Agent mining studies ways of interaction and integration between data mining and agents. This area brought advances to the technologies involved such as theories, methodologies, and solutions. AgentGeo is one such technology enhancement consisting of relevant functions to extract knowledge from spatial databases. Satellite image mining promotes advances in the state of art of agent mining.